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To PhD, or not to PhD, that is the question

Reading a paper by a Carnegie Mellon computer science professor about Ph.D's qualifications, it appears they only recruit candidates with deep interests in academic research; which is understandable. It also said a Ph.D is generally a waste of time if trying to enhance your job prospect. Again, completely understandable. However, when I read about HFT, I always come across sentences such as "mathematical and computer science Ph.D's writing sophisticated algorithms". Even while reading through HFT job offerings, they seem to prefer CS Ph.D's.

Is there not a slight disconnect between academia's Ph.D recruitment qualifications and HFT firms preferences? Why would top computer science Ph.D programs prefer those who want to remain in academia knowing that they're preferences for them outside of it? Or is it because those in HFT firms focus a large part of their time researching and developing specific algorithms before finally implementing them. So by recruiting Ph.D's, the firm knows the candidate already possesses the ability to understake rigorous research?
 
First you have to realize that those job postings are probably from recruiters and not the actual firm. It's probably easier for a recruiter to sell a PhD to a firm because of the mystique around having a PhD.

PhD programs' goal is to train researchers. For finance that generally is limited to academia, but for computer science that could mean academia or industry research. Why want their PhD students to remain in academia? I'm sure each professor has their own reasons; some believe that the work they are doing is more important and/or world changing then working a regular 9-5.

HFT is highly technical, and that level of knowledge/expertise is hard to come by. You can't be an iPhone app developer for a few years and have the skills to go into HFT. It requires relevant experience (for example, real time telecom router programming) or years spent researching a narrow relevant subject (i.e. PhD).
 
Well, the answer is something in the middle. Firms on Wall Street are employing their own research teams to conduct a research on their issues of interest and mainly require the team members to be PhDs. For the career path there is not a hard pressure to be PhD and masters degrees are enough depending on what you are intending to go to. But anyway, it is better to hold it I think whether or not you are going to stay in academia. Time is one huge factor to consider. Generally, people switching from other career find it hard to devote so much time to PhD programs and want to make a kind of a "shortcut" to specialization so they mainly push towards masters. Here is a small extract from one of my favorite books: Emanuel Derman - My Life As A Quant.

Wall Street had never been a place for academics.Yet, from the
day I got to Goldman in late 1985, I kept hearing people talk
with awe about Fischer Black, codiscoverer of the Black-
Scholes equation for options pricing and the head of Goldman’s
Quantitative Strategies group.....

Derman also describes many interesting things about academia and industry. Interesting read.
 

Yike Lu

Finder of biased coins.
There is nothing wrong with doing a PhD then going into finance.

But the idea of doing a PhD in a technical field SPECIFICALLY to get into finance is backwards. Remember that in the course of getting your PhD, you are spending 5 years of your life on a single topic. It is absolutely not a good decision if you do not like the topic of choice.
 
Hi all,
I am wondering if it is possible for a PhD in RFIC Design Engineering ( Radio Frequency Integrated Circuits design, part of the field of Electrical Engineering) to move into Quant Finance or are they only looking for Maths/Physics/Stats/CS type of people. Do you think an RFIC designer's skill is relevant in Quant finance? Also is UC Berkeley considered a top-tier school for PhD recruitment in Quants?
Thanks so much for your help!
 
D

Deleted member 2387

While Derman's book is the face that launched a thousand ships, I fear it is grossly anachronistic. My personal observation is that recruiters, HR or otherwise need to reevaluate what a quantitative PhD 'IS'. Top school or otherwise. If hiring managers are interested more in 'product placement' type of approach to hiring PhDs, doom is on the cards.
 
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